CN115291216B - Satellite-borne SAR image acquisition method and device, electronic equipment and medium - Google Patents

Abstract

The invention provides a spaceborne SAR image acquisition method, device, electronic equipment and medium, and relates to the technical field of synthetic aperture radar. The specific implementation method includes: obtaining the spaceborne SAR echo data for the target area, the target area includes N _target target sub-areas; for each target sub-area, according to the spaceborne SAR echo data and the satellite trajectory model, determine The trajectory mapping relationship of the first target sub-region corresponding to the sub-region; according to the spaceborne SAR echo data and the satellite trajectory model, determine the trajectory mapping relationship of multiple first target regions corresponding to the target region; according to the N _target first target sub-region The trajectory mapping relationship and the plurality of first target area trajectory mapping relationships determine a second target area trajectory mapping relationship corresponding to the target area; and according to the second target area trajectory mapping relationship and the spaceborne SAR echo data for the target area, determine Spaceborne SAR imagery for the target area.

Description

Space-borne SAR image acquisition method, device, electronic equipment and medium

technical field

The invention relates to the technical field of synthetic aperture radar, in particular to a spaceborne SAR image acquisition method, device, electronic equipment, storage medium and computer program product.

Background technique

In the field of spaceborne synthetic aperture radar (SAR) imaging technology, satellite trajectory error is one of the main factors affecting the image quality of spaceborne SAR.

The satellite trajectory error mainly refers to the deviation between the measured value of the satellite platform position and the actual value, which will cause the error of the instantaneous slant distance. The instantaneous slant distance is an important parameter for constructing the azimuth matched filter, so its deviation will make the azimuth matched filter mismatch, resulting in loss of resolution and decrease of signal-to-noise ratio. In addition, the instantaneous slant distance is also related to the calculation of the target's position, and its error will also affect the target positioning accuracy. Therefore, when the spaceborne SAR trajectory error is large, the problem of defocusing of the SAR image usually occurs, thereby reducing the quality of the SAR image.

Contents of the invention

The present invention provides a spaceborne SAR image acquisition method, device, electronic equipment, storage medium and computer program product, in order to at least partly solve the above existing technical problems.

According to one aspect of the present invention, a method for acquiring a spaceborne SAR image is provided, including: acquiring spaceborne SAR echo data for a target area, wherein the target area includes N _target target sub-areas, and N _target is greater than or equal to 3 Integer of ; for each target sub-area in the N _target target sub-areas, according to the spaceborne SAR echo data, determine the track point of the satellite corresponding to the N ₁ azimuth moments within the imaging time of the target sub-area, And according to N ₁ trajectory points and the satellite trajectory model, determine the trajectory mapping relationship of the first target sub-region corresponding to the target sub-region, N ₁ is an integer greater than or equal to 3; according to the spaceborne SAR echo data, the imaging in the target region Determine the trajectory points of the satellites corresponding to the N ₂ azimuth moments in time, and determine the trajectory mapping relationship of a plurality of first target areas corresponding to the target area according to the N ₂ trajectory points and the satellite trajectory model, where N ₂ is greater than or equal to 5 Integer; according to the N _target first target sub-area track mapping relationship and a plurality of first target area track mapping relationships, determine the second target area track mapping relationship corresponding to the target area; and according to the second target area track mapping relationship and Based on the spaceborne SAR echo data of the target area, the spaceborne SAR image of the target area is determined.

According to an embodiment of the present invention, according to the N ₁ track points and the satellite track model, determining the first target sub-area track mapping relationship corresponding to the target sub-area includes: for each track point in the N ₁ track points, according to the track point and the length of the first step, determine a plurality of first reference trajectory points associated with the trajectory point; according to N ₁ trajectory points and a plurality of first reference trajectory points associated with N ₁ trajectory points, multiple The first trajectory point combination; according to multiple first trajectory point combinations and satellite trajectory models, determine a plurality of second target sub-region trajectory mapping relationships corresponding to the target sub-region; and from multiple second target sub-region trajectory mapping relationships Determine the target sub-area track optimization mapping relationship as the first target sub-area track mapping relationship.

According to an embodiment of the present invention, according to the N ₁ trajectory points and the satellite trajectory model, determining the first target sub-region trajectory mapping relationship corresponding to the target sub-region further includes: responding to the trajectory mapping relationship from multiple second target sub-regions If the target sub-area trajectory optimization mapping relationship is not matched, update the first step size to the second step size; and based on the second step size, repeatedly perform the determination of the target sub-region trajectory optimization mapping relationship from multiple second target sub-region trajectory mapping relationships relation as an operation of the first target subregion trajectory mapping relation.

According to an embodiment of the present invention, determining the optimal mapping relationship of the trajectory of the target sub-area from the multiple second target sub-area trajectory mapping relationships includes: respectively using the multiple second target sub-area trajectory mapping relationships and the onboard corresponding to the target sub-area The SAR echo data performs imaging processing on the target sub-region to obtain multiple complex image data; according to the multiple complex image data, multiple imaging contrasts are obtained; and in response to triggering of preset conditions, the maximum imaging contrast among the multiple imaging contrasts is obtained The corresponding second target sub-area trajectory mapping relationship is used as the target sub-region trajectory optimization mapping relationship.

According to an embodiment of the present invention, the preset condition includes at least one of the following: the increase of the maximum imaging contrast obtained in this optimization compared with the maximum imaging contrast obtained in the previous optimization is less than or equal to the first threshold; and The step size corresponding to the sub-optimization is less than or equal to the second threshold.

According to an embodiment of the present invention, for N _target first target sub-area track mapping relationships and multiple first target area track mapping relationships, determining the second target area track mapping relationship corresponding to the target area includes: for the N _target first For each of the target sub-area trajectory mapping relationships, determine the trajectory points of the satellites corresponding to N _orb azimuth moments within the imaging time of the target sub-region, and determine N _orb trajectories based on the first target sub-region trajectory mapping relationship Point and the slant distance between the central target point of this target sub-area, obtain the first slant distance of N _orb ; N _orb is the integer greater than or equal to 3; For each in a plurality of first target area trajectory mapping relations, based on The first target area trajectory mapping relationship determines the slant distances under N _orb azimuth moments corresponding to each target sub-area in N _target target sub-areas, and obtains N _target * N _orb second slant distances, for multiple For each of the first target area trajectory mapping relations, determine the degree of deviation between the N _target *N _orb second slant distances and the N _orb first slant distances of the N _target first target sub-region trajectory mapping relations; and Based on the degree of deviation, the optimized mapping relationship of the trajectory of the target area is determined as the second mapping relationship of the trajectory of the target area from the plurality of mapping relationships of the trajectory of the first target area.

According to an embodiment of the present invention, according to the N ₂ track points and the satellite track model, determining a plurality of first target area track mapping relationships corresponding to the target area includes: for each track point in the N ₂ track points, according to the track point and the third step length, determine a plurality of second reference trajectory points associated with the trajectory point; according to N ₂ trajectory points and a plurality of second reference trajectory points associated with N ₂ trajectory points, a plurality of a second track point combination; and determining multiple first target area track mapping relationships corresponding to the target area according to the multiple second track point combinations and the satellite track model.

According to an embodiment of the present invention, for N _target first target sub-area track mapping relationships and multiple first target area track mapping relationships, determining the second target area track mapping relationship corresponding to the target area further includes: responding to , from the multiple first target area trajectory mapping relationships that do not match the target area trajectory optimization mapping relationship, update the third step size to the fourth step size; and based on the fourth step size, repeatedly execute In the mapping relationship, the optimal mapping relationship of the target area trajectory is determined as the operation of the second target area trajectory mapping relationship.

According to an embodiment of the present invention, based on the degree of deviation, determining the optimal mapping relationship of the trajectory of the target area from the plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship includes: determining the minimum deviation degree from the plurality of deviation degrees; And in response to the minimum degree of deviation being less than or equal to the third threshold, the first target area trajectory mapping relationship corresponding to the minimum deviation degree is determined as the target area trajectory optimization mapping relationship.

According to an embodiment of the present invention, based on the degree of deviation, determining the optimal mapping relationship of the trajectory of the target area from the plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship includes: determining the minimum deviation degree from the plurality of deviation degrees; And in response to the fact that the step size corresponding to this optimization is less than or equal to the fourth threshold, the first target area trajectory mapping relationship corresponding to the minimum deviation degree is determined as the target area trajectory optimization mapping relationship.

According to another aspect of the present invention, a space-borne SAR image acquisition device is provided, including: an acquisition module for acquiring space-borne SAR echo data for a target area, wherein the target area includes N _target target sub-areas, N _target is an integer greater than or equal to 3; the first mapping module is used to determine each target sub-region in the N _target target sub-regions according to the satellite-borne SAR echo data within the imaging time of the target sub-region The trajectory point of the satellite corresponding to N ₁ azimuth moments, and according to N ₁ trajectory points and the satellite trajectory model, determine the first target sub-region trajectory mapping relationship corresponding to the target sub-region, N ₁ is an integer greater than or equal to 3; The second mapping module is used to determine the trajectory points of the satellites corresponding to the N ₂ azimuth moments within the imaging time of the target area according to the spaceborne SAR echo data, and determine the corresponding satellite trajectory points according to the N ₂ trajectory points and the satellite trajectory model. A plurality of first target area track mapping relationships corresponding to the target area, N ₂ is an integer greater than or equal to 5; a determination module is used to track mapping relationships according to N _target first target sub-areas and a plurality of first target area track mapping relationships , determining a second target area trajectory mapping relationship corresponding to the target area; and an imaging module, configured to determine a spaceborne SAR image for the target area according to the second target area trajectory mapping relationship and the spaceborne SAR echo data for the target area .

According to another aspect of the present invention, an electronic device is provided, including: one or more processors; a memory for storing one or more programs, wherein, when the one or more programs are executed by the one or When multiple processors are executed, one or more processors are executed to implement the above-mentioned method.

According to another aspect of the present invention, there is provided a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor is executed to implement the method as described above.

According to another aspect of the present invention there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method as described above.

Description of drawings

In order to further illustrate the technical content of the present invention, it will be described in detail below in conjunction with examples and accompanying drawings, wherein:

Fig. 1 is the flow chart of the spaceborne SAR image acquisition method according to the embodiment of the present invention;

2 is a schematic diagram of a method for determining a plurality of first reference track points associated with each track point according to an embodiment of the present invention;

Fig. 3 is an imaging model in the process of determining the optimal mapping relationship of the trajectory of the target sub-region according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a method for finding an optimal mapping relationship for a target sub-region trajectory according to an embodiment of the present invention;

FIG. 5 is a flowchart of a method for determining the trajectory mapping relationship of the second target area according to an embodiment of the present invention;

FIG. 6A and FIG. 6B are simulation experiment results before the method of the present invention is used to improve the imaging image quality of the target sub-region;

Fig. 7, Fig. 8A to Fig. 8D are respectively the simulation experiment results of improving the image quality of point target imaging by using the method of the present invention;

Fig. 9 is the imaging result of the point target in the target area before adopting the method of the present invention to process;

Figures 10A to 10E are the results of improving the imaging quality of each point target by using the optimal trajectory estimation of the target area;

11 is a block diagram of a spaceborne SAR image acquisition device according to an embodiment of the present invention; and

Fig. 12 is a block diagram of electronic equipment used to implement the method for acquiring a spaceborne SAR image according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments and the drawings in the embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

It should be noted that the sequence number of each operation in the following methods is only used as a representation of the operation for description, and should not be regarded as representing the execution sequence of the respective operations. The methods do not need to be performed in the exact order presented, unless explicitly stated otherwise.

Fig. 1 is a flowchart of a method for acquiring a spaceborne SAR image according to an embodiment of the present invention.

As shown in FIG. 1 , the method for acquiring a spaceborne SAR image includes operations S110 to S150.

In operation S110, spaceborne SAR echo data for a target area is acquired, wherein the target area includes N _target sub-areas.

In operation S120, for each target sub-region in the N _target target sub-regions, according to the satellite-borne SAR echo data, determine the trajectory points of the satellites corresponding to the N ₁ azimuth moments within the imaging time of the target sub-region , and according to the N ₁ trajectory points and the satellite trajectory model, determine the trajectory mapping relationship of the first target sub-region corresponding to the target sub-region.

In operation S130, according to the satellite-borne SAR echo data, within the imaging time of the target area, determine the track points of the satellites corresponding to the N ₂ azimuth moments, and determine the points corresponding to the target area according to the N ₂ track points and the satellite track model. Multiple first target area trajectory mapping relationships.

In operation S140, a second target area trajectory mapping relationship corresponding to the target area is determined according to the N _target first target sub-area trajectory mapping relationships and the plurality of first target area trajectory mapping relationships.

In operation S150, a spaceborne SAR image for the target area is determined according to the trajectory mapping relationship of the second target area and the spaceborne SAR echo data for the target area.

According to an embodiment of the present invention, the target area may include, for example, N _target target sub-areas, where N _target is an integer greater than or equal to 3. The spaceborne SAR echo data for the target area includes spaceborne SAR echo data for N _{target target} subareas. Wherein, the spaceborne SAR echo data for each target subregion can be used for imaging processing of the target subregion, and the spaceborne SAR echo data for each target region can be used for imaging processing of the target region .

According to the embodiment of the present invention, since the trajectory of the spaceborne SAR satellite is a smooth curve, according to this feature, the satellite trajectory model can be used to describe the trajectory history of the satellite within the imaging time of the target area (or target sub-area). Considering that the spaceborne SAR trajectory error has low-order error characteristics, the polynomial coefficients in the satellite trajectory model can be used to correct the satellite trajectory error, thereby improving the imaging quality of the spaceborne SAR echo data.

Since the trajectory of the spaceborne SAR satellite is a smooth curve, the trajectory of the satellite in the imaging time of the target area (or target sub-area) can be regarded as composed of a series of trajectory points, each trajectory point is used to represent The instantaneous position of the satellite at the corresponding azimuth instant. Subsequently, multiple trajectory points can be selected from these trajectory points to fit the polynomial coefficients of the optimal satellite trajectory model, and the polynomial coefficients can be applied to the satellite trajectory model to obtain the trajectory mapping of the target area (or target sub-area) relationship, and then use the trajectory mapping relationship of the target area (or target sub-area) for imaging processing to obtain the spaceborne SAR image for the target area (or target sub-area). The so-called optimal polynomial coefficients of the satellite trajectory model here means that the satellite trajectory model obtained based on the polynomial coefficients has the smallest trajectory error under certain conditions.

Based on the above mechanism, for each target sub-region, the track points of satellites corresponding to N ₁ azimuth moments can be determined from the satellite-borne echo data for the target sub-region within the imaging time of the target sub-region, N ₁ is an integer greater than or equal to 3. Next, the trajectory mapping relationship of the first target sub-area corresponding to the target sub-area may be determined according to the N ₁ track points and the satellite track model. Wherein, the trajectory mapping relationship of the first target sub-region is the optimal trajectory estimation for the target sub-region, which describes the trajectory history of the satellite with the minimum satellite trajectory error within the imaging time of the target sub-region. The imaging error of the target sub-region can be corrected by using the trajectory mapping relationship of the first target sub-region.

According to an embodiment of the present invention, for the target area, within the imaging time of the target area, the trajectory points of the satellites corresponding to N ₂ azimuth moments are determined from the spaceborne SAR echo data for the target area, and N ₂ is greater than or equal to Integer of 5. Then, according to the N ₂ track points and the satellite track model, a plurality of first target area track mapping relationships corresponding to the target area are determined. Wherein, the first target area trajectory mapping relationship is a potential optimal trajectory estimation for the target area, which describes the potential trajectory history of the satellite with the minimum satellite trajectory error within the imaging time of the target area.

It can be understood that the trajectory mapping relationship of the first target sub-region is the optimal trajectory estimation for the target sub-region, which actually reflects the slant distance history closest to the real situation within the imaging time of the target sub-region. After acquiring the N _target first target sub-area track mapping relationships and multiple first target area track mapping relationships, N _target first target sub-area track mapping relationships can be used to determine from the multiple first target area track mapping relationships The trajectory mapping relationship of the second target area corresponding to the target area. Wherein, the second target area trajectory mapping relationship is an optimal trajectory estimation for the target area, which describes the trajectory history of the satellite with the minimum satellite trajectory error within the imaging time of the target area. The imaging error of the target area can be corrected by using the trajectory mapping relationship of the second target area, so as to improve the quality of the spaceborne SAR image for the target area.

Next, imaging processing may be performed according to the trajectory mapping relationship of the second target area and the space-borne SAR echo data of the target area, so as to determine the space-borne SAR image of the target area. It can be understood that in the embodiments of the present invention, any one or more suitable methods can be adopted to perform spaceborne SAR imaging processing (including imaging processing for the target area and target sub-area), which can be selected according to actual needs, The present invention is not limited thereto.

In the solution of the embodiment of the present invention, based on the characteristics of satellite orbit smoothness, using the satellite orbit model and multiple trajectory points, respectively determine the trajectory mapping relationship of the first target sub-region corresponding to multiple target sub-regions, and based on the multiple A target sub-area trajectory mapping relationship determines the second target area trajectory mapping relationship corresponding to the target area from multiple first target area trajectory mapping relationships, so as to obtain the optimal trajectory estimation for the local area and the overall area, which can ensure that the area corresponds Accurate estimation and compensation of slant range errors within imaging time improves the quality of spaceborne SAR images.

According to an embodiment of the present invention, in the above operation S120, according to the N ₁ trajectory points and the satellite trajectory model, determining the trajectory mapping relationship of the first target sub-region corresponding to the target sub-region may include the following operations.

For each track point in the N ₁ track points, according to the track point and the first step length, determine a plurality of first reference track points associated with the track point; according to the N ₁ track points and the N ₁ track points A plurality of first reference track points associated with each other obtain a plurality of first track point combinations; according to a plurality of first track point combinations and a satellite track model, determine a plurality of second target sub-area track maps corresponding to the target sub-area relationship; and determine the optimal mapping relationship of the trajectory of the target sub-area from the plurality of second target sub-area trajectory mapping relationships as the first target sub-area trajectory mapping relationship.

Fig. 2 is a schematic diagram of a method for determining a plurality of first reference track points associated with each track point according to an embodiment of the present invention. The following will take the track point P as an example to illustrate an example process of determining a plurality of first reference track points associated with the track point P. FIG.

As shown in Figure 2, in the space three-dimensional coordinate system xyz, the y direction represents the azimuth direction of the satellite trajectory, that is, the track direction. The (x-z) plane represents the plane perpendicular to the track direction.

For example, for the trajectory point P, its corresponding coordinates on the (x-z) plane are (x, z). Take this track point P as the center and take the first step length n as the step size, set up the grid as shown in Figure 2 and take the value, a plurality of first reference track points associated with the track point P can be obtained, for example the first A reference track point P1, a first reference track point P2, a first reference track point P3 and a first reference track point P4. The corresponding coordinates of the first reference trajectory points P1 to P4 on the (x-z) plane are (x, z+η), (x+η, z), (x, z-η), (x-η, z) .

Similarly, for any other track point among the N1 track points, the above method may be used to determine multiple _first reference track points associated with these track points. The subsequent N ₁ track points and their corresponding first reference track points may be used to form multiple first track point combinations.

According to an embodiment of the present invention, the first track point combination is a track point set composed of track points corresponding to N ₁ azimuth moments or first reference track points. The number of first track point combinations is determined by the number of track points and the number of first reference track points associated with the track points.

For example, assuming that the track points corresponding to N1 azimuth moments include track point P, track point G, and track point M, where there are four _first reference track points associated with each track point, then the first track point The number of combinations is 5 ³ . In one example, the first track point combination can be expressed as (P, G, M), (P, G1, M1), or (P2, G, M1), etc., where P2, G1 and M1 are track The first reference track point of point P, track point G and track point M.

According to the embodiment of the present invention, according to the combination of the first trajectory points, a group of polynomial coefficients of the satellite trajectory model can be obtained by fitting, and the polynomial coefficients can be applied to the satellite trajectory model to obtain the second target sub-region corresponding to the target sub-region Track mapping relationship. There is a one-to-one correspondence between the first track point combination and the second target sub-area track mapping relationship.

In one example, the satellite trajectory model can be represented by the following formula (1).

（1）

(1)

In formula (1), (X _s , Y _s , Z _s ) represents the instantaneous position of the satellite, N-1 represents the polynomial order of the satellite trajectory model, t represents the azimuth sampling time, (a _n , b _n , c _n ) (n=0,…,N-1) represent the polynomial coefficients in the satellite trajectory model. Wherein, N may be determined according to the number of track points in the first track point combination.

According to the first trajectory point combination and the satellite trajectory model shown in the above formula (1), the expression of the polynomial coefficient of the satellite trajectory model can be obtained. It should be noted that the solving process of the polynomial coefficients a _n , b _n and c _n is similar. In order to save space, the polynomial coefficient a _{n is} taken as an example to illustrate the solving process of the polynomial coefficients.

In the embodiment of the present invention, the expression of the polynomial coefficient a _n of the satellite trajectory model shown in the formula (2) can be obtained by solving the first track point combination and the satellite track model shown in the above formula (1).

（2）

(2)

、A和L_a分别可以采用以下公式（3）~（5）来表示。in,

, A and L _a can be represented by the following formulas (3)~(5) respectively.

（3）

(3)

（4）

(4)

（5）

(5)

表示多项式系数在x方向上的分量的矩阵表达，A表示根据 选取的方位时刻所生成的大小为N*N的系数矩阵，L_a表示N个方位时刻时卫星的瞬时位置在 x方向上的分量，T表示矩阵转置，t_i（i=1,…,N）表示第i个方位向采样时刻，X_Si（i=1,…,N） 表示第i个方位时刻卫星的瞬时位置在x方向上的位置坐标，a_n（n=0,…,N-1）表示卫星在x 方向上的位置坐标随方位时刻变化的多项式各阶系数。 In formulas (2)~(5),

Represents the matrix expression of the components of polynomial coefficients in the x direction, A represents the coefficient matrix of size N*N generated according to the selected azimuth time, L _a represents the component of the satellite's instantaneous position in the x direction at N azimuth times , T represents the matrix transpose, t _i (i=1,…,N) represents the i-th azimuth sampling moment, X _Si (i=1,…,N) represents the instantaneous position of the satellite at the i-th azimuth moment at x The position coordinates in the direction, a _n (n=0,…,N-1) represent the polynomial coefficients of each order of the position coordinates of the satellite in the x direction that change with the azimuth moment.

Similarly, the polynomial coefficients b _n and c _n can be obtained according to the solution method of the polynomial coefficient a _n , and the polynomial coefficients b _n and c _n respectively have similar expressions to the polynomial coefficient a _n , and will not be repeated here.

Next, after obtaining the polynomial coefficients a _n , b _n and c _n , the polynomial coefficients a _n , b _n and c _n can be applied to the above formula (1) to obtain the second target sub-region trajectory corresponding to the target sub-region Mapping relations. Similarly, using the method described above, multiple second target sub-area track mapping relationships corresponding to the target sub-area can be determined according to the combination of multiple first track points and the satellite track model.

According to an embodiment of the present invention, determining the optimal mapping relationship of the trajectory of the target sub-region from the plurality of mapping relationships of the trajectory of the second target sub-region may include the following operations.

Using multiple second target sub-area trajectory mapping relationships and spaceborne SAR echo data corresponding to the target sub-area to perform imaging processing on the target sub-area to obtain multiple complex image data; according to the multiple complex image data, multiple Imaging contrast; and in response to the triggering of preset conditions, using the second target sub-region track mapping relationship corresponding to the maximum imaging contrast among the multiple imaging contrasts as the target sub-region track optimization mapping relationship.

According to an embodiment of the present invention, different first trajectory point combinations can be fitted to obtain respective corresponding second target sub-region trajectory mapping relationships. The trajectory mapping relationship of each second target sub-region is a preliminary trajectory estimate for the target sub-region, which describes the potential trajectory history of the satellite with the minimum satellite trajectory error within the imaging time of the target sub-region. Each trajectory history may produce different slant range histories for the same target sub-area, resulting in different instantaneous slant range errors, which ultimately manifest as differences in imaging quality.

In order to reduce the satellite trajectory error in the imaging process of the target sub-area, minimize the slant distance error in the imaging process of the target sub-area, and optimize the focusing effect of the imaging results, multiple second target sub-areas can be selected based on the maximum contrast criterion. The optimal mapping relationship of the target sub-area trajectory is determined in the regional trajectory mapping relationship, and the optimal mapping relationship of the target sub-region trajectory is used as the first target sub-region trajectory mapping relationship.

According to the embodiment of the present invention, multiple complex image data can be obtained by performing imaging processing on the target sub-regions by utilizing trajectory mapping relationships of multiple second target sub-regions and spaceborne SAR echo data corresponding to the target sub-regions. From multiple complex image data, multiple imaging contrasts can be obtained.

In one example, the imaging contrast can be determined using equation (6) below.

（6）

(6)

表示成像对比度，

表示复图像幅值的方差，

表示复图像幅值的均值，

表示复图像数据。 In formula (6),

Indicates the imaging contrast,

Indicates the variance of the complex image magnitude,

Indicates the mean value of the complex image amplitude,

Represents complex image data.

According to an embodiment of the present invention, the variance of the complex image magnitude and the mean of the complex image magnitude may be determined from the complex image data. In one example, the variance of the complex image magnitude and the mean of the complex image magnitude may be determined using the following equations (7) and (8), respectively.

（7）

(7)

（8）

(8)

In formulas (7) and (8), k represents the sampling time in the range direction, t represents the sampling time in the azimuth direction, and M represents the pixel size of the complex image.

Based on the above formulas (6)-(8), multiple imaging contrasts respectively corresponding to the multiple complex image data can be obtained according to the multiple complex image data. If the preset condition is met, the second target sub-region trajectory mapping relationship corresponding to the maximum imaging contrast can be determined from multiple imaging contrasts based on the maximum contrast criterion, and used as the target sub-region trajectory optimization mapping relationship.

In some embodiments, if the preset condition is not satisfied, the optimal target sub-area track mapping relationship cannot be matched from multiple second target sub-area trajectory mapping relationships, that is, the optimal target corresponding to the target sub-area cannot be found. Sub-area trajectory mapping relationship. In this case, the first step size can be updated to the second step size, and based on the second step size, repeatedly determine the target sub-region trajectory optimization mapping relationship from multiple second target sub-region trajectory mapping relationships as the first Operations on the trajectory mapping relationship of the target subregion. If the target sub-area track optimal mapping relationship can be determined from multiple second target sub-area track mapping relationships based on the second step size, the target sub-area track optimal mapping relationship is used as the first target sub-area track mapping relationship. It should be noted that, based on the second step length, the process of determining the optimal mapping relationship of the trajectory of the target sub-region as the first target sub-region trajectory mapping relationship from multiple second target sub-region trajectory mapping relationships is different from that based on the first step length from multiple The process of determining the optimal trajectory mapping relationship of the target sub-region in the second target sub-region trajectory mapping relationship as the first target sub-region trajectory mapping relationship is similar, and will not be repeated here.

According to an embodiment of the present invention, multiple second step sizes may be set to perform multiple rounds of optimization. For example, in the case that a second step size does not match the optimal mapping relationship of the target sub-area trajectory, another second step size can also be used for optimization; the operation is repeated until a target sub-region trajectory optimization mapping is determined The relationship is used as the first target sub-region trajectory mapping relationship, or it is determined that there is no target sub-region trajectory optimization mapping relationship.

According to an embodiment of the present invention, the above-mentioned preset conditions include at least one of the following: the increase of the maximum imaging contrast obtained by this optimization compared with the maximum imaging contrast obtained by the previous optimization is less than or equal to the first threshold, and the step size corresponding to this optimization is less than or equal to the second threshold. It can be understood that the first threshold and the second threshold and the first step size and the second step size may be set according to actual conditions, which is not limited in the present invention.

An example process of finding the optimal mapping relationship of the trajectory of the target sub-region will be described below with reference to FIG. 3 and FIG. 4 .

Fig. 3 is an imaging model in the process of determining the optimal mapping relationship of the trajectory of the target sub-region according to an embodiment of the present invention.

As shown in FIG. 3 , the y direction represents the azimuth direction of the satellite trajectory, that is, the track direction. The (x-z) plane represents the plane perpendicular to the track direction. Point Q represents the central target point of the target sub-area. The satellite flies along the y direction, and the actual flight trajectory of a satellite can be determined (as shown by the dotted line in Figure 3). A number of trajectory points are determined from the actual trajectory within the imaging time frame of the target sub-region. According to the plurality of trajectory points, an ideal trajectory can be obtained by fitting (as shown by the solid line in FIG. 3 ).

In Fig. 3, _Re and R _s represent the error-containing slant distance and the actual slant distance at the central target point Q, respectively. By comparing R _e and R _s , it can be seen that due to the existence of satellite trajectory error, the error of instantaneous slant distance will be caused. The error of the instantaneous slant distance will affect the target positioning accuracy, and then reduce the quality of SAR image.

As mentioned above, the trajectory of the spaceborne SAR satellite can be regarded as a smooth curve. Based on this feature, the satellite trajectory model can be used to describe the satellite orbit position. In addition, considering the low-order error characteristics of the spaceborne SAR trajectory error, the polynomial coefficients in the satellite trajectory model can be used to correct the satellite trajectory error, thereby improving the imaging quality of the spaceborne SAR echo data. Therefore, the trajectory history problem of solving the minimum satellite trajectory error can be transformed into finding a set of optimal polynomial coefficients of the satellite trajectory model. However, the order of coefficients of polynomials in the satellite trajectory model differs greatly, and the linear and constant terms cannot be searched. Therefore, it is impossible to search and optimize the polynomial coefficients directly. In the embodiment of the present invention, the polynomial coefficients can be optimized by using the method of searching for the position of the iterative trajectory point, so as to obtain the optimal mapping relationship of the target sub-region trajectory, and then use the optimal mapping relationship of the target sub-region trajectory to improve the spaceborne SAR echo Data imaging quality.

Fig. 4 is a schematic diagram of a method for finding an optimal mapping relationship of a trajectory of a target sub-region according to an embodiment of the present invention.

As shown in FIG. 4 , the method for finding the optimal mapping relationship of the trajectory of the target sub-region includes operations S401-S409.

In operation S401, N ₁ trajectory points are acquired. According to an embodiment of the present invention, within the imaging time of the target sub-area, the track points of the satellites corresponding to N ₁ azimuth moments are determined from the spaceborne SAR echo data, N ₁ is an integer greater than or equal to 3, and N ₁ are obtained track point.

In operation S402, the first step length is obtained. According to an embodiment of the present invention, the length of the first step may be set according to actual conditions, which is not limited in the present invention.

In operation S403, a plurality of first trajectory point combinations are determined.

According to an embodiment of the present invention, for each of the N ₁ track points, a plurality of first reference track points associated with the track point can be determined according to the track point and the length of the first step, and according to N ₁ track point and a plurality of first reference track points respectively associated with the N ₁ track points to obtain a plurality of first track point combinations. The manner of determining the combination of the first reference track point and the first track point is similar to the process described above, and will not be repeated here.

In operation S404, a plurality of second target sub-region trajectory mapping relationships are determined. According to an embodiment of the present invention, based on the above formulas (1) to (5), multiple second target sub-region trajectory mapping relationships can be obtained by fitting according to the combination of multiple first trajectory points.

In operation S405, a plurality of complex image data is determined.

For example, multiple complex image data can be obtained by performing imaging processing on the target sub-region by using the trajectory mapping relationships of the plurality of second target sub-regions and the spaceborne SAR echo data corresponding to the target sub-region.

In operation S406, a plurality of imaging contrasts are determined. According to an embodiment of the present invention, based on the above formulas (6) to (8), multiple imaging contrasts can be determined according to multiple complex image data.

In operation S407, it is judged whether the preset condition is satisfied, if yes, perform operation S408, otherwise, perform operation S409.

The preset conditions may include at least one of the following: it is determined that the increase of the maximum imaging contrast obtained by this optimization compared to the maximum imaging contrast obtained by the previous optimization is less than or equal to the first threshold, and the corresponding The step size is less than or equal to the second threshold. If the preset condition is met, perform operation S408, otherwise, perform operation S409.

In operation S408, the trajectory mapping relationship of the second target sub-region corresponding to the maximum imaging contrast among the plurality of imaging contrasts is used as the optimized mapping relationship of the trajectory of the target sub-region.

In operation S409, the first step size is updated to the second step size, and operations S403-S407 are repeatedly performed until the optimal mapping relationship of the trajectory of the target sub-area is determined.

According to an embodiment of the present invention, if the preset condition is not satisfied, it means that no matching optimal mapping relationship of the trajectory of the target sub-region has been found. At this point, the first step size can be updated to the second step size, and operations S403-407 are repeated until the optimal mapping relationship of the trajectory of the target sub-area is determined. Then, the trajectory optimization mapping relationship of the target sub-region is used as the first target sub-region trajectory mapping relationship, so that the satellite-borne SAR echo data imaging of the target sub-region can be corrected by using the first target sub-region trajectory mapping relationship, thereby improving the target Spaceborne SAR image quality in the sub-regional imaging time range.

According to an embodiment of the present invention, in the above operation S130, according to the N ₂ trajectory points and the satellite trajectory model, determining multiple first target area trajectory mapping relationships corresponding to the target area may include the following operations.

For each track point in the N ₂ track points, according to the track point and the third step, determine a plurality of second reference track points associated with the track point; according to the N ₂ track points and the N ₂ track points A plurality of second reference track points associated respectively, to obtain a plurality of second track point combinations; and according to a plurality of second track point combinations and the satellite track model, determining a plurality of first target area track mapping relationships corresponding to the target area .

In the embodiment of the present invention, the process of determining the second reference track point, the second track point combination, and the multiple first target area track mapping relationships is respectively the same as determining the first reference track point, the first track point combination, and the multiple second track point combinations. The process of the trajectory mapping relationship of the target sub-area is the same or similar, and will not be described here in order to save space.

According to the embodiment of the present invention, the trajectory mapping relationship of the first target sub-region is the optimal trajectory estimation for the target sub-region, which actually reflects the slope distance history closest to the real situation within the imaging time of the target sub-region. However, within the imaging time range for the target area, the sensitivity to satellite trajectory errors varies with different imaging geometries. In order to obtain the optimal trajectory estimation for the target area and improve the quality of the spaceborne SAR image for the target area, after obtaining the trajectory mapping relationship of the first target sub-area respectively corresponding to the N _target sub-areas, use N The _target first target sub-area track mapping relationship is used to determine a second target area track mapping relationship for the target area, so as to use the second target area track mapping relationship to improve image quality within the imaging time range of the target area.

Fig. 5 is a flowchart of a method for determining a trajectory mapping relationship of a second target area according to an embodiment of the present invention.

As shown in FIG. 5 , the method for determining the trajectory mapping relationship of the second target area includes operations S541 to S544.

In operation S541, for each of the N _target first target sub-area trajectory mapping relationships, determine the track points of the satellites corresponding to the N _orb azimuth moments within the imaging time of the target sub-area, and based on the first target sub-area The trajectory mapping relationship is to determine the slant distances between the N _orb trajectory points and the central target point of the target sub-area respectively, and obtain the N _orb first slant distances.

In operation S542, for each of the plurality of first target area trajectory mapping relationships, N _orb azimuth moments corresponding to each target subregion in the N _target target subregions are determined based on the first target region trajectory mapping relationship The next slant distance, get N _target *N _orb second slant distances.

In operation S543, for each of the plurality of first target area trajectory mapping relationships, N _orb first slant distances of N _target *N _orb second slant distances and N _target first target sub-region trajectory mapping relationships are determined deviation between.

In operation S544, based on the degree of deviation, an optimized target area trajectory mapping relationship is determined as a second target area trajectory mapping relationship from the plurality of first target area trajectory mapping relationships.

According to an embodiment of the present invention, the target area includes N _target target sub-areas, and each of the N _target target sub-areas corresponds to a trajectory mapping relationship of the first target sub-area. For each first target sub-region trajectory mapping relationship, determine the satellite trajectory points corresponding to N _orb azimuth moments within the imaging time of the target sub-region, N _orb is an integer greater than or equal to 3. Then, based on the trajectory mapping relationship of the first target sub-area, the slope distances between the N _orb track points and the central target point of the target sub-area are respectively determined to obtain N _orb first slope distances. Using the above method, N _target *N _orb first slant distances can be obtained based on the trajectory mapping relationship of the N _target first target sub-areas.

According to an embodiment of the present invention, for each first target area trajectory mapping relationship, according to the first target area trajectory mapping relationship, N _orb orientations corresponding to each target sub-region in the N _target target sub-regions can be determined The slant distance at the moment, and N _target *N _orb second slant distances are obtained.

It can be understood that the first target area trajectory mapping relationship is a potential optimal trajectory estimation for the target area, which describes the potential trajectory history of the satellite with the minimum satellite trajectory error within the imaging time of the target area. The trajectory mapping relationship of the first target sub-region is the optimal trajectory estimation for the target sub-region. If the overall trajectory represented by the first target region trajectory mapping relationship within the target region imaging time and the local trajectory within the target subregion imaging time represented by the N _target first target subregion trajectory mapping relationship can be well matched combined, so that the deviation between the slant distance history of the target under the overall trajectory estimation and the slant distance history under the optimal trajectory estimation of the target subregion in each target subregion is as small as possible, then the trajectory of the first target region The mapping relationship is more likely to be the optimal trajectory estimation for the target area.

Based on this mechanism, the N _target *N _orb first oblique distances obtained based on the N _target first target sub-area trajectory mapping relationship and the N _target *N _orb second oblique distances obtained based on the first target area trajectory mapping relationship The degree of deviation between distances is determined from multiple first target area trajectory mapping relationships to determine the target area trajectory optimization mapping relationship as the second target area trajectory mapping relationship.

It can be understood that, based on the trajectory mapping relationship of each first target area, a degree of deviation can be determined. Therefore, multiple degrees of deviation can be determined according to multiple first target area trajectory mapping relationships.

According to an embodiment of the present invention, determining the target area trajectory optimization mapping relationship as the second target area trajectory mapping relationship from multiple first target area trajectory mapping relationships based on the degree of deviation may include the following operations: determining the minimum deviation from the multiple deviation degrees degree, and in the case that the minimum degree of deviation is less than or equal to the third threshold, the first target area trajectory mapping relationship corresponding to the minimum deviation degree is determined as the target area trajectory optimization mapping relationship. In this way, it is realized that the optimal mapping relationship of the trajectory of the target area is determined from the plurality of mapping relationships of the trajectory of the first target area as the second mapping relationship of the trajectory of the target area.

In some embodiments, determining the target area trajectory optimization mapping relationship as the second target area trajectory mapping relationship from multiple first target area trajectory mapping relationships based on the degree of deviation may also include the following operations: determining the minimum deviation from the multiple deviation degrees Degree, in the case that the step size corresponding to this optimization is less than or equal to the fourth threshold, the first target area trajectory mapping relationship corresponding to the minimum deviation degree is determined as the target area trajectory optimization mapping relationship. In this way, it is realized that the optimal mapping relationship of the trajectory of the target area is determined from the plurality of mapping relationships of the trajectory of the first target area as the second mapping relationship of the trajectory of the target area.

According to an embodiment of the present invention, if the target area trajectory optimization mapping relationship is not matched based on the degree of deviation, the third step size can be updated to the fourth step size during the process of determining multiple first target area trajectory mapping relationships, and Based on the fourth step, the operation of determining the optimal trajectory mapping relationship of the target area from the plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship is repeatedly performed. If based on the fourth step, the optimal trajectory mapping relationship of the target area can be determined from the plurality of first target area trajectory mapping relationships, the optimal trajectory mapping relationship of the target area is used as the second target area trajectory mapping relationship. It should be noted that the process of determining the optimal trajectory mapping relationship of the target area from multiple first target area trajectory mapping relationships based on the fourth step length as the second target area trajectory mapping relationship is the same as determining the optimal trajectory mapping relationship of the target area from multiple first target area trajectory mapping relationships based on the third step length. The process of determining the optimal trajectory mapping relationship of the target region as the second trajectory mapping relationship of the target region in the trajectory mapping relationship of the target region is similar and will not be repeated here.

According to an embodiment of the present invention, multiple fourth step sizes may be set to perform multiple rounds of optimization. For example, in the case that a fourth step does not match the optimal mapping relationship of the trajectory of the target area, another fourth step can also be used for optimization; the operation is repeated until an optimal mapping relationship of the trajectory of the target area is determined as The second target area trajectory mapping relationship, or determine that there is no target area trajectory optimization mapping relationship.

According to an embodiment of the present invention, the degree of deviation mentioned above may be variance, difference, deviation, standard deviation, etc., which is not limited in the present invention.

It should be noted that the above-mentioned third threshold, fourth threshold, third step size, and fourth step size may be set according to actual needs, which is not limited in the present invention.

In the embodiment of the present invention, the second target area trajectory mapping relationship corresponding to the target area is determined from the multiple first target area trajectory mapping relationships based on the multiple first target sub-area trajectory mapping relationships, so as to obtain the optimal target area for the target area. The optimal trajectory estimation can ensure the accurate estimation and compensation of the slant range error corresponding to the imaging time of the target area, and improves the quality of the spaceborne SAR image within the imaging time range of the target area.

In order to enable those skilled in the art to understand the technical solutions of the present invention more clearly, the advantages of the present invention will be described below in conjunction with specific examples.

In the embodiment of the present invention, the main radar parameters of the simulation experiment are shown in Table 1. As shown in Table 1, the main radar parameters of the simulation experiment include carrier frequency, modulation frequency, sampling frequency, pulse width, pulse repetition frequency, oblique angle of view and synthetic aperture time. Among them, the carrier frequency is 9.6GHz, the modulation frequency is 1.1×10 ¹³ Hz/s, the sampling frequency is 133333333Hz, the pulse width is 9.24 μs , the pulse repetition frequency is 4567Hz, the oblique angle is 0°, and the synthetic aperture time is about 1s.

Table 1

FIG. 6A and FIG. 6B are simulation experiment results before the method of the present invention is used to improve the imaging quality of the target sub-region. It should be noted that, for simplicity of description, the target sub-region is referred to as a point target below, which will not be described in detail later.

Fig. 6A is the imaging result of a point target before being processed by the method of the present invention. As shown in Figure 6A, due to the influence of the satellite trajectory error, the imaging image of the point target has obvious defocus phenomenon in the azimuth direction.

Fig. 6B is an azimuth sectional view of a point target corresponding to Fig. 6A. According to the azimuth profile of the point target shown in Figure 6B, due to the influence of the satellite trajectory error, the main lobe and side lobes are seriously aliased and cannot be distinguished, which affects the resolution of the point target in the azimuth direction.

FIG. 7 , and FIG. 8A to FIG. 8D are simulation experiment results of using the method of the present invention to improve the image quality of point target imaging.

In the process of improving the image quality of point target imaging by using the method of the invention, an error perpendicular to the course is added to the satellite track point. The trajectory points at five azimuth moments are selected within the point target imaging time, and for each of the five trajectory points, four first reference trajectory points associated with the trajectory point are determined. According to the 5 track points and the corresponding 20 first reference track points, 5 to ⁵ first track point combinations are obtained. Next, the trajectory mapping relationship of the first target sub-area is determined by using the combination of 5 to ⁵ first track points, and imaging processing is performed on the spaceborne SAR echo data corresponding to the point target based on the trajectory mapping relationship of the first target sub-area, and the point Target imaging results.

In the embodiment of the present invention, different step length strategies are used for optimization, and the increase of imaging contrast is less than 10 ^-2 as the stop condition to find the trajectory mapping relationship of the first target sub-region corresponding to the point target. And the point target is imaged based on the trajectory mapping relationship of the first target sub-area, and the imaging results shown in FIG. 7, FIG. 8A to FIG. 8D are obtained. Among them, Figure 7 shows the imaging results of the initial step size of 1m, each iteration is reduced by 0.2m, and stopped after 2 iterations (hereinafter referred to as the first step length strategy). Figures 8A to 8D show the imaging results of a fixed step size of 0.2 m and stopping after 8 iterations (hereinafter referred to as the second step size strategy).

Please refer to Fig. 6A, Fig. 6B and Fig. 7 together. Compared with the imaging results of the previous point targets processed by the method of the present invention, the imaging results obtained with the first step length strategy can significantly improve the scatter of the point targets in the azimuth direction. The focusing problem of the point target has been greatly improved. Moreover, the method of the invention can clearly distinguish the main lobe and the side lobe, and improves the resolution of the point target in the azimuth direction. Thus, the quality of spaceborne SAR images is improved.

Similarly, by comparing Fig. 6A with Fig. 8A and Fig. 8B, it can be seen that the imaging result obtained by the second step length strategy can also significantly improve the defocusing problem of the point target in the azimuth direction, and the focus degree of the point target has been well improved. In addition, by comparing FIG. 6B with FIG. 8C and FIG. 8D , it can be seen that the method of the present invention can clearly distinguish the main lobe and the side lobe, and improve the resolution of the point target in the azimuth direction. This improves the quality of spaceborne SAR images.

In the embodiment of the present invention, the results of improving the image quality of point target imaging by using two step length strategies are also compared, and the comparison results are shown in Table 2.

Table 2

In the embodiment of the present invention, the peak side lobe ratio, the integral side lobe ratio and the imaging contrast can be used to evaluate the improvement of the imaging quality of the point target. As shown in Table 2, the peak sidelobe ratio and integral sidelobe ratio obtained by using the first step strategy are -13.255dB and -9.79dB respectively, and the peak sidelobe ratio and integral sidelobe ratio obtained by using the second step strategy are The lobe ratios are -13.258dB and -9.79dB, respectively. It can be understood that the peak sidelobe ratio obtained by using the first step size strategy and the second step size strategy is close to -13.26dB, and the integral sidelobe ratio is close to -10dB, which can meet the image focusing requirements. In addition, the peak sidelobe ratio, integral sidelobe ratio and imaging contrast obtained by using the first step length strategy are better than the peak sidelobe ratio, integral sidelobe ratio and imaging contrast obtained by using the second step length strategy. Consistency, which is consistent with the imaging results shown in Fig. 7, Fig. 8A to Fig. 8D, indicating that the method of the present invention has good adaptability, and different step length strategies can be used to improve the image quality of point target imaging. To improve the quality of spaceborne SAR images.

In some embodiments, the method of the present invention can also be used to improve the imaging image quality of multiple point targets in the target area. This will be described in detail below in conjunction with specific embodiments.

Fig. 9 is the imaging result of a point target in the target area before processing by the method of the present invention.

As shown in FIG. 9 , the target area includes 5 point objects, such as point object A, point object B, point object C, point object D, and point object E. All point targets are affected by satellite trajectory errors, and there is defocus in the azimuth direction.

In order to improve the imaging quality of each point target in the target area, the method of the present invention is used to optimize the trajectory, and the optimal trajectory estimation (that is, the trajectory mapping relationship of the first target sub-area) in the case of each point target can be obtained. The corresponding target imaging The quality improvement is shown in Table 3. As shown in Table 3, the peak sidelobe ratio corresponding to each point target is basically close to -13.26dB, and the integral sidelobe ratio is basically close to -10dB, which can meet the image focus requirements, and the focus degree of each point target in the target area can be obtained. improvement.

table 3

It can be understood that the optimal trajectory estimation result corresponding to each point target represents the estimation result closest to the actual trajectory within the synthetic aperture time of the corresponding point target. According to the method of the present invention, the trajectory points of satellites corresponding to 3 azimuth moments can be selected for each point target within the synthetic aperture time, and the first slant distance under the corresponding optimal estimated trajectory can be calculated to obtain the slant distances at 15 azimuth moments. first slope distance.

Next, based on the 15 azimuth moments and the first slant distance of the corresponding point target, the trajectory points at the corresponding 15 azimuth moments can be selected within the imaging time of the target area, and the slant distance error is the smallest. The optimal condition is used to fit the optimal trajectory estimation for the target area (that is, the trajectory mapping relationship of the second target area). And the optimal trajectory estimation of the target area is used to improve the imaging quality of each point target in the target area, and the results shown in Table 4 and FIGS. 10A to 10E are obtained.

Table 4

Table 4 is the result of improving the imaging quality of each point target in the target area by using the optimal trajectory estimation of the target area. 10A to 10E are the results of improving the imaging quality of each point target by using the optimal trajectory estimation of the target area.

As shown in Table 4 and Figures 10A to 10E, using the optimal trajectory estimation of the target area to improve the imaging quality of each point target in the target area can significantly improve the focusing effect of each point target. Moreover, by comparing Table 3 and Table 4, it can be seen that using the optimal trajectory estimation of the target area to improve the imaging quality of each point target, the optimal trajectory estimation corresponding to each point target has a better effect on the improvement of its own imaging quality. consistency.

Based on the above-mentioned space-borne SAR image acquisition method, the present invention also provides a space-borne SAR image acquisition device.

Fig. 11 schematically shows a block diagram of a spaceborne SAR image acquisition device according to an embodiment of the present invention.

As shown in FIG. 11 , in the embodiment of the present invention, the spaceborne SAR image acquisition device 1100 may include an acquisition module 1110 , a first mapping module 1120 , a second mapping module 1130 , a determination module 1140 and an imaging module 1150 .

The acquisition module 1110 is used to acquire spaceborne SAR echo data for a target area, wherein the target area includes N _target target sub-areas, and N _target is an integer greater than or equal to 3.

The first mapping module 1120 is used for each target sub-region in the N _target target sub-regions, according to the satellite-borne SAR echo data, determine the satellites corresponding to the N ₁ azimuth moments within the imaging time of the target sub-region track points, and according to N ₁ track points and the satellite track model, determine the first target sub-area track mapping relationship corresponding to the target sub-area, N ₁ is an integer greater than or equal to 3.

The second mapping module 1130 is used to determine the trajectory points of the satellites corresponding to the N ₂ azimuth moments within the imaging time of the target area according to the spaceborne SAR echo data, and determine the corresponding satellite trajectory points according to the N ₂ trajectory points and the satellite trajectory model. The trajectory mapping relationship of multiple first target areas corresponding to the target area, N ₂ is an integer greater than or equal to 5.

The determining module 1140 is configured to determine a second target area trajectory mapping relationship corresponding to the target area according to the N _target first target sub-area trajectory mapping relationships and multiple first target area trajectory mapping relationships.

The imaging module 1150 is configured to determine a spaceborne SAR image for the target area according to the trajectory mapping relationship of the second target area and the spaceborne SAR echo data for the target area.

It should be noted that the implementations of modules/units/subunits, etc., the technical problems solved, the functions realized, and the technical effects achieved in the embodiments of the device part are respectively the same as those of the corresponding steps in the embodiments of the method part. , the technical problems solved, the functions realized, and the technical effects achieved are the same or similar, and will not be repeated here.

According to an embodiment of the present invention, any number of modules in the acquisition module 1110, the first mapping module 1120, the second mapping module 1130, the determination module 1140, and the imaging module 1150 can be combined into one module, or any one of them Can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the acquisition module 1110, the first mapping module 1120, the second mapping module 1130, the determination module 1140 and the imaging module 1150 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), programmable logic array (PLA), system-on-chip, system-on-substrate, system-on-package, application-specific integrated circuit (ASIC), or any other reasonable means by which circuits can be integrated or packaged, such as hardware or firmware, or any one of software, hardware, and firmware, or an appropriate combination of any of them. Alternatively, at least one of the acquisition module 1110, the first mapping module 1120, the second mapping module 1130, the determination module 1140 and the imaging module 1150 may be at least partially implemented as a computer program module, and when the computer program module is executed, the Execute the corresponding function.

According to the embodiments of the present invention, the present invention also provides an electronic device, a readable storage medium and a computer program product.

According to an embodiment of the present invention, an electronic device includes: at least one processor; and a memory communicatively connected to at least one processor; wherein, the memory stores instructions executable by at least one processor, and the instructions are processed by at least one The processor is executed, so that at least one processor can perform the method as described above.

According to an embodiment of the present invention, a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method as described above.

According to an embodiment of the present invention, a computer program product includes a computer program, and the computer program implements the above method when executed by a processor.

Fig. 12 schematically shows a block diagram of an electronic device adapted to implement the method for acquiring a spaceborne SAR image according to an embodiment of the present invention.

As shown in FIG. 12 , an electronic device 1200 according to an embodiment of the present invention includes a processor 1201 that can be loaded into a random access memory (RAM) 1203 according to a program stored in a read-only memory (ROM) 1202 or from a storage section 1208 Various appropriate actions and processing are performed by the program. The processor 1201 may include, for example, a general-purpose microprocessor (eg, a CPU), an instruction set processor and/or a related chipset, and/or a special-purpose microprocessor (eg, an application-specific integrated circuit (ASIC)), and the like. Processor 1201 may also include on-board memory for caching purposes. The processor 1201 may include a single processing unit or multiple processing units for executing different actions of the method flow according to the embodiment of the present invention.

In the RAM 1203, various programs and data necessary for the operation of the electronic device 1200 are stored. The processor 1201 , ROM 1202 , and RAM 1203 are connected to each other through a bus 1204 . The processor 1201 executes various operations of the method flow according to the embodiment of the present invention by executing programs in the ROM 1202 and/or RAM 1203 . It should be noted that the program may also be stored in one or more memories other than the ROM 1202 and the RAM 1203 . The processor 1201 may also execute various operations of the method flow according to the embodiment of the present invention by executing the programs stored in the one or more memories.

According to an embodiment of the present invention, the electronic device 1200 may further include an input/output (I/O) interface 1205 which is also connected to the bus 1204 . The electronic device 1200 may also include one or more of the following components connected to the I/O interface 1205: an input part 1206 including a keyboard, a mouse, etc.; including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. An output section 1207 of a speaker or the like; a storage section 1208 including a hard disk or the like; and a communication section 1209 including a network interface card such as a LAN card, a modem, or the like. The communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to the I/O interface 1205 as needed. A removable medium 1211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 1210 as necessary so that a computer program read therefrom is installed into the storage section 1208 as necessary.

The present invention also provides a computer-readable storage medium. The computer-readable storage medium may be included in the device/apparatus/system described in the above embodiments; it may also exist independently without being assembled into the device/system device/system. The above-mentioned computer-readable storage medium carries one or more programs, and when the above-mentioned one or more programs are executed, the method according to the embodiment of the present invention is implemented.

According to an embodiment of the present invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as but not limited to: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM) , erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present invention, a computer-readable storage medium may include one or more memories other than ROM 1202 and/or RAM 1203 and/or ROM 1202 and RAM 1203 described above.

Embodiments of the present invention also include a computer program product, which includes a computer program including program codes for executing the methods shown in the flowcharts. When the computer program product runs in the computer system, the program code is used to make the computer system realize the method for acquiring satellite-borne SAR images provided by the embodiment of the present invention.

When the computer program is executed by the processor 1201, the above-mentioned functions defined in the system/device of the embodiment of the present invention are performed. According to the embodiments of the present invention, the above-described systems, devices, modules, units, etc. may be implemented by computer program modules.

In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program can also be transmitted and distributed in the form of a signal on network media, downloaded and installed through the communication part 1209, and/or installed from the removable media 1211. The program code contained in the computer program can be transmitted by any appropriate network medium, including but not limited to: wireless, wired, etc., or any appropriate combination of the above.

In such an embodiment, the computer program may be downloaded and installed from a network via communication portion 1209 and/or installed from removable media 1211 . When the computer program is executed by the processor 1201, the above-mentioned functions defined in the system of the embodiment of the present invention are executed. According to the embodiments of the present invention, the above-described systems, devices, devices, modules, units, etc. may be implemented by computer program modules.

According to the embodiments of the present invention, the program codes for executing the computer programs provided by the embodiments of the present invention can be written in any combination of one or more programming languages, specifically, high-level procedural and/or object-oriented programming language, and/or assembly/machine language to implement these computing programs. Programming languages include, but are not limited to, programming languages such as Java, C++, python, "C" or similar programming languages. The program code can execute entirely on the user computing device, partly on the user device, partly on the remote computing device, or entirely on the remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (for example, using an Internet service provided business to connect via the Internet).

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or portion of code that includes one or more logical functions for implementing specified executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block in the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations, can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a A combination of dedicated hardware and computer instructions.

Those skilled in the art can understand that the features described in the various embodiments of the present invention can be combined and/or combined in various ways, even if such a combination or combination is not explicitly recorded in the present invention. In particular, without departing from the spirit and teaching of the present invention, the features described in the various embodiments of the present invention can be combined and/or combined in various ways. All such combinations and/or combinations fall within the scope of the present invention.

The embodiments of the present invention have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the various embodiments have been described separately above, this does not mean that the measures in the various embodiments cannot be advantageously used in combination. Those skilled in the art can make various substitutions and modifications without departing from the scope of the present invention, and these substitutions and modifications should all fall within the scope of the present invention.

Claims (12)

1. A satellite-borne SAR image acquisition method is characterized by comprising the following steps:

acquiring satellite-borne SAR echo data for a target region, wherein the target region comprises N _target A target sub-region, N _target Is an integer of 3 or more;

for N _target Determining N target sub-regions in the imaging time of each target sub-region according to the satellite-borne SAR echo data ₁ The track points of the satellite corresponding to each azimuth moment are determined according to N ₁ Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the track points and the satellite track model, N ₁ Is an integer of 3 or more;

determining N within the imaging time of the target area according to the satellite-borne SAR echo data ₂ The track points of the satellite corresponding to each azimuth moment are determined according to N ₂ Determining a plurality of first target area track mapping relations corresponding to the target areas by the track points and the satellite track model, N ₂ Is an integer of 5 or more;

according to N _target Determining a second target area track mapping relation corresponding to the target area according to the first target sub-area track mapping relation and the first target area track mapping relations;

determining a satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area;

said according to N _target Determining a second target area track mapping relationship corresponding to the target area, wherein the first target area track mapping relationship and the second target area track mapping relationship comprise:

for N _target A first target sub-regionEach of the trajectory mapping relationships is determined with N during an imaging time of the target sub-region _orb The track points of the satellite corresponding to the azimuth time are determined respectively based on the track mapping relation of the first target sub-area _orb The slant distance between each track point and the central target point of the target sub-area is obtained to obtain N _orb A first pitch; n is a radical of hydrogen _orb Is an integer of 3 or more;

for each of a plurality of first target area trajectory mapping relationships, determining N based on the first target area trajectory mapping relationship _target N corresponding to each target sub-region in each target sub-region _orb The slope distance at each azimuth moment is obtained as N _target *N _orb A second slope distance is set between the first slope distance and the second slope distance,

determining the N for each of a plurality of first target area trajectory mapping relationships _target *N _orb A second slope distance and N _target N of track mapping relation of first target sub-regions _orb A degree of deviation between the first slope distances; and

and determining a target area track optimization mapping relation from a plurality of first target area track mapping relations as the second target area track mapping relation based on the deviation degree.

2. The method of claim 1, wherein the method is based on N ₁ Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the track points and the satellite track model, wherein the first target sub-region track mapping relation comprises:

for N ₁ Each track point in the track points determines a plurality of first reference track points associated with the track point according to the track point and the first step length;

according to N ₁ A track point and N ₁ A plurality of first reference track points which are respectively associated with the plurality of track points are obtained to obtain a plurality of first track point combinations;

determining a plurality of second target sub-region track mapping relations corresponding to the target sub-regions according to the plurality of first track point combinations and the satellite track model; and

and determining a target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as the first target sub-region track mapping relation.

3. The method of claim 2, wherein the function N is ₁ Determining a first target sub-region track mapping relationship corresponding to the target sub-region by using the track points and the satellite track model, and further comprising:

in response to not matching the target sub-region track optimization mapping relationship from among the plurality of second target sub-region track mapping relationships, updating the first step size to a second step size; and

and based on the second step size, repeatedly executing the operation of determining a target sub-region track optimization mapping relation from the plurality of second target sub-region track mapping relations as the first target sub-region track mapping relation.

4. The method of claim 2 or 3, wherein determining a target sub-region trajectory optimization mapping from the plurality of second target sub-region trajectory mappings comprises:

respectively using the plurality of second target sub-region track mapping relations and satellite-borne SAR echo data corresponding to the target sub-regions to perform imaging processing on the target sub-regions to obtain a plurality of complex image data;

obtaining a plurality of imaging contrasts according to the plurality of complex image data; and

responding to the trigger of a preset condition, and taking a second target sub-region track mapping relation corresponding to the maximum imaging contrast in the multiple imaging contrasts as the target sub-region track optimization mapping relation.

5. The method of claim 4, wherein the preset condition comprises at least one of:

the increment of the maximum imaging contrast obtained by the optimization relative to the maximum imaging contrast obtained by the previous optimization is less than or equal to a first threshold; and

the step length corresponding to the optimization is less than or equal to a second threshold value.

6. The method of claim 1, wherein the method is based on N ₂ Determining a plurality of first target area track mapping relationships corresponding to the target area, including:

for N ₂ Determining a plurality of second reference track points associated with each track point according to the track point and the third step length;

according to N ₂ A track point and N ₂ The plurality of track points are respectively associated with a plurality of second reference track points to obtain a plurality of second track point combinations; and

and determining a plurality of first target area track mapping relations corresponding to the target area according to the plurality of second track point combinations and the satellite track model.

7. The method of claim 6, wherein the function N is _target Determining a second target area trajectory mapping relationship corresponding to the target area further includes:

in response to not matching the target region trajectory optimization mapping from the plurality of first target region trajectory mapping relationships to the target region trajectory optimization mapping relationship based on the degree of deviation, updating the third step size to a fourth step size; and

based on the fourth step size, repeatedly executing the operation of determining the target area track optimization mapping relation from the plurality of first target area track mapping relations as the second target area track mapping relation.

8. The method according to claim 1, 6 or 7, wherein the determining a target area trajectory optimization mapping relationship from a plurality of first target area trajectory mapping relationships as the second target area trajectory mapping relationship based on the degree of deviation comprises:

determining a minimum degree of deviation from a plurality of degrees of deviation; and

and determining a first target area track mapping relation corresponding to the minimum deviation degree as the target area track optimization mapping relation in response to the minimum deviation degree being smaller than or equal to a third threshold value.

9. The method of claim 7, wherein determining a target region trajectory optimization mapping from a plurality of first target region trajectory mapping relationships as the second target region trajectory mapping relationship based on the degree of deviation comprises:

determining a minimum degree of deviation from the plurality of degrees of deviation; and

and determining the first target area track mapping relation corresponding to the minimum deviation degree as the target area track optimization mapping relation in response to that the step length corresponding to the optimization is smaller than or equal to a fourth threshold value.

10. A satellite-borne SAR image acquisition device is characterized by comprising:

an acquisition module for acquiring spaceborne SAR echo data for a target region, wherein the target region comprises N _target A target sub-region, N _target Is an integer of 3 or more;

a first mapping module for mapping N _target Determining N target sub-regions in the imaging time of each target sub-region according to the satellite-borne SAR echo data ₁ The track points of the satellite corresponding to each azimuth moment are determined according to N ₁ Determining a first target sub-region track mapping relation corresponding to the target sub-region by using the track points and the satellite track model, N ₁ Is an integer of 3 or more;

a second mapping module for imaging the target region within the imaging time according to the satellite-borne SAR echo dataDetermining the sum of N ₂ The track points of the satellite corresponding to each azimuth moment are determined according to N ₂ Determining a plurality of first target area track mapping relations corresponding to the target areas by the track points and the satellite track model, N ₂ Is an integer of 5 or more;

a determination module for determining according to N _target Determining a second target area track mapping relation corresponding to the target area according to the first target sub-area track mapping relation and the first target area track mapping relations;

the imaging module is used for determining a satellite-borne SAR image aiming at the target area according to the second target area track mapping relation and the satellite-borne SAR echo data aiming at the target area;

the determination module is further to:

for N _target Each of a first target sub-region trajectory mapping relationship is determined with N within an imaging time of the target sub-region _orb The track points of the satellite corresponding to the azimuth time are determined respectively based on the track mapping relation of the first target sub-area _orb The slant distance between each track point and the central target point of the target sub-area is obtained to obtain N _orb A first pitch; n is a radical of hydrogen _orb Is an integer of 3 or more;

determining N for each of a plurality of first target area trajectory mappings based on the first target area trajectory mapping _target N corresponding to each target sub-region in each target sub-region _orb The slope distance at each azimuth moment is obtained as N _target *N _orb A second slope distance is set between the first slope distance and the second slope distance,

determining the N for each of a plurality of first target area trajectory mapping relationships _target *N _orb A second slope distance and N _target N of track mapping relation of first target sub-regions _orb A degree of deviation between the first slope distances; and

and determining a target area track optimization mapping relation from a plurality of first target area track mapping relations as the second target area track mapping relation based on the deviation degree.

11. An electronic device, comprising:

one or more processors;

a memory for storing one or more programs,

wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1 to 9.

12. A computer-readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 9.

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